Senior AI Systems & Platform Engineer (m/f/d)
Indexed description
Group/Division
Enabling the movement toward advanced chip design, KLA's Measurement, Analytics and Control group (MACH) is looking for the best and brightest research scientists, software engineers, application development engineers and senior product technology process engineers to join our team. The MACH team's mission is to collaborate with our customers to innovate technologies and solutions that detect and control highly complex process variations—at their source—rather than compensate for them at later stages of the manufacturing process. With over 40 years of semiconductor process control experience, chipmakers around the globe rely on KLA to ensure that their fabs ramp next-generation devices to volume production quickly and cost-effectively. Our MACH team develops leading-edge solutions for patterning process analytics and control technologies, thereby providing customers with critical insight at the feature level, field level and cross-wafer analysis. Our teams also develop advanced modeling simulation, data analytics and process control modeling technologies. As a member of the MACH team, you’ll be joining the most sophisticated and successful process-control company in the semiconductor industry--working across functions to solve the most complex technical problems in the digital age.
Job Description/Preferred Qualifications
Solution Architecture & Platform Engineering
- Define end-to-end architecture for on-prem / air gapped AI platforms, including compute, storage, networking, and model serving layers.
- Design and implement portable AI infrastructure using open-source components (model serving, orchestration, vector storage, pipelines).
- Translate product requirements into scalable system architectures, including deployment topology and hardware sizing.
- Establish security, isolation, and resilience patterns for AI workloads in restricted environments.
- Own decisions on model hosting, orchestration, observability, and lifecycle management.
- Design and deploy agentic and multi-agent systems on top of production-grade infrastructure.
- Integrate reasoning, planning, and learning capabilities into reliable, observable, and maintainable systems.
- Collaborate with hardware, software, and data teams to ensure seamless deployment and usability in production environments.
- Drive integration of AI systems into existing products and workflows in semiconductor manufacturing.
- Continuously evaluate and adapt emerging AI and infrastructure technologies for real-world industrial use cases.
- Guide architectural decisions around AI infrastructure, model deployment, and system evolution.
- Contribute to building internal standards and reusable components for AI engineering across the division.
- University degree in Computer Science, Electrical Engineering, or a related field.
- Strong experience in solution architecture and system design for production-grade software systems.
- Expertise in deploying AI/ML systems in on-premise, air gapped, or otherwise restricted environments.
- Hands-on experience with:
- Model serving and inference systems (e.g. vLLM or similar).
- Distributed systems, high-performance computing, or data-intensive platforms.
- CI/CD and MLOps for offline or partially connected environments.
- Ability to define and evaluate hardware requirements (GPU/CPU/memory/storage/networking) for AI workloads.
- Strong programming skills (Python required; experience with systems-level languages such as C/C++ or Rust is a plus).
- Fluent communication in English.
- Experience building cloud-independent AI platforms or migrating workloads away from managed cloud services.
- Familiarity with composing AI stacks from open-source components rather than relying on managed services.
- Experience with agent-based systems, reinforcement learning, or LLM-based applications.
- Understanding of semiconductor manufacturing processes and data pipelines.
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